SPCards

SPCards evaluates and annotates splicing variants to predict splicing effects, benchmark splicing prediction methods, and support high-throughput identification of non-canonical and ambiguous splicing variants.

Key Features:

• Performance Evaluation: Performs benchmarking of differential splicing analysis methods using approximately 50,000 positive and negative splicing variants sourced from over 8,000 studies.
• Predictive Accuracy: Analyzes method performance across donor and acceptor splicing regions and applies region-specific weight coefficients, reporting that 66.67% of evaluated methods exhibited higher specificity than sensitivity to inform cut-off selection.
• Integration and Validation: Validates integration potential of splicing prediction methods using correlation metrics and consistent prediction ratios.
• Comprehensive Annotation: Provides variant-level and gene-level annotations including allele frequency data, non-synonymous predictions, and a range of functional insights.
• High-Throughput Capability: Enables high-throughput genetic identification of splicing variants, including variants in non-canonical splicing regions.

Scientific Applications:

• Method benchmarking: Comparative evaluation of splicing prediction and differential splicing analysis methods.
• Variant interpretation: Prioritization and functional interpretation of splicing variants for studies of genetic disorders.
• Clinical and personalized genomics: Informing cut-off selection and variant impact assessment relevant to personalized medicine workflows.
• Evolutionary and regulatory studies: Investigating splicing mechanisms and their effects on gene regulation and expression.

Methodology:

Curation of splicing variant data from literature sources; integration with genomic prediction algorithms; benchmarking of differential splicing analysis methods using ~50,000 positive and negative variants from >8,000 studies; calculation of specificity and sensitivity metrics, region-specific weight coefficients for donor/acceptor analysis, correlation metrics and prediction ratios; annotation with allele frequency and non-synonymous prediction data.